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Estimation of the spatial weights matrix under structural constraints

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  • Bhattacharjee, Arnab
  • Jensen-Butler, Chris
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    Abstract

    While estimates of models with spatial interaction are very sensitive to the choice of spatial weights, considerable uncertainty surrounds the definition of spatial weights in most studies with cross-section dependence. We show that, in the spatial error model, the spatial weights matrix is only partially identified, and is fully identified under the structural constraint of symmetry. For the spatial error model, we propose a new methodology for estimation of spatial weights under the assumption of symmetric spatial weights, with extensions to other important spatial models. The methodology is applied to regional housing markets in the UK, providing an estimated spatial weights matrix that generates several new hypotheses about the economic and socio-cultural drivers of spatial diffusion in housing demand.

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    Bibliographic Info

    Article provided by Elsevier in its journal Regional Science and Urban Economics.

    Volume (Year): 43 (2013)
    Issue (Month): 4 ()
    Pages: 617-634

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    Handle: RePEc:eee:regeco:v:43:y:2013:i:4:p:617-634

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    Web page: http://www.elsevier.com/locate/regec

    Related research

    Keywords: Spatial econometrics; Spatial autocorrelation; Spatial weights matrix; Spatial error model; Partial identification; Housing demand; Gradient projection;

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    References

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    Cited by:
    1. Abhimanyu Gupta & M. Robinson, 2013. "Inference on Higher-Order Spatial Autoregressive Models with Increasingly Many Parameters," Economics Discussion Papers 735, University of Essex, Department of Economics.
    2. Arnab Bhattacharjee & Eduardo Castro & Taps Maiti & João Marques, 2014. "Endogenous spatial structure and delineation of submarkets: A new framework with application to housing markets," SEEC Discussion Papers 1403, Spatial Economics and Econometrics Centre, Heriot Watt University.

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